Package: diffcyt
Version: 1.2.23
Title: Differential discovery in high-dimensional cytometry via
        high-resolution clustering
Description: Statistical methods for differential discovery analyses in high-dimensional cytometry data (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry), based on a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics.
Authors@R: person("Lukas M.", "Weber", email = "lukmweber@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3282-1730"))
URL: https://github.com/lmweber/diffcyt
BugReports: https://github.com/lmweber/diffcyt/issues
License: MIT + file LICENSE
biocViews: ImmunoOncology, FlowCytometry, Proteomics, SingleCell,
        CellBasedAssays, CellBiology, Clustering, FeatureExtraction,
        Software
Depends: R (>= 3.4.0)
Imports: flowCore, FlowSOM, SummarizedExperiment, S4Vectors, limma,
        edgeR, lme4, multcomp, dplyr, tidyr, reshape2, magrittr, stats,
        methods, utils, grDevices, graphics, ComplexHeatmap, circlize,
        grid
VignetteBuilder: knitr
Suggests: BiocStyle, knitr, rmarkdown, testthat, HDCytoData, CATALYST
RoxygenNote: 6.1.1
git_url: https://git.bioconductor.org/packages/diffcyt
git_branch: RELEASE_3_8
git_last_commit: 8bdfd18
git_last_commit_date: 2019-04-04
Date/Publication: 2019-04-04
NeedsCompilation: no
Packaged: 2019-04-05 03:55:04 UTC; biocbuild
Author: Lukas M. Weber [aut, cre] (<https://orcid.org/0000-0002-3282-1730>)
Maintainer: Lukas M. Weber <lukmweber@gmail.com>
Built: R 3.5.3; ; 2019-04-05 10:45:02 UTC; windows
